Frank Sehnke

Zentrum für Sonnenenergie- und Wasserstoff-Forschung Baden-Württemberg — Germany

Engineering · Physical Sciences

13h-index2.6kcitations47works0.52yr avg
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Research Topics

Fuel Cells and Related Materials(11), Reinforcement Learning in Robotics(8), Energy Load and Power Forecasting(6), Physical Unclonable Functions (PUFs) and Hardware Security(6), Cell Image Analysis Techniques(4)

Publications47 total

Back to the Future: A LSTM Based Approach for Fuel Cell Degradation Prediction and Anomaly Detection
Journal of The Electrochemical Society·2025
Age Ain’t Just a Number: Leveraging Recurrent Neural Networks to Predict Fuel Cell Degradation
ECSarXiv (OSF Preprints)·2025
Age Ain’t Just a Number: Leveraging Recurrent Neural Networks to Predict Fuel Cell Degradation
2025
The Voltage Oracle: A Foundation Model for Probabilistic PEM Fuel Cell Voltage Prediction
Journal of The Electrochemical Society·2025· 1 citedOpen Access
Big Brother Is Watching You: Leveraging Artificial Intelligence for Automated Fuel Cell Monitoring (Technical Report)
ECS Meeting Abstracts·2024
Big Brother is Watching You: Leveraging Artificial Intelligence for Automated Fuel Cell Monitoring (Technical Report)
2024
Big Brother Is Watching You: Leveraging Artificial Intelligence for Automated Fuel Cell Monitoring (Technical Report)
ECS Transactions·2024
Big Brother Is Watching You: Leveraging Artificial Intelligence for Automated Fuel Cell Monitoring (Technical Report)
ECS Transactions·2024· 3 cited
A Fuel Cell’s Big Brother: Artificial Intelligence for Monitoring Fuel Cells
ECS Meeting Abstracts·2023
Lifelong performance monitoring of PEM fuel cells using machine learning models
Journal of Power Sources·2023· 13 cited
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
Energies·2023· 7 citedOpen Access
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
Preprints.org·2023· 3 citedOpen Access
Entwicklung und Erprobung eines Systems zur Vermeidung von potenziellen Auswirkungen auf Vögel durch die Windenergienutzung
Open MIND·2023
Brücke zwischen Forschung und Anwendung
BWK ENERGIE·2022
Lifelong Performance Monitoring of Pem Fuel Cells Using Machine Learning Models
SSRN Electronic Journal·2022· 1 citedOpen Access
Probabilistic short term wind power forecasts using deep neural networks with discrete target classes
Advances in geosciences·2018· 9 citedOpen Access
Probabilistic short term wind power forecasts with using Deep Neural Networks with discrete target classes
EGU General Assembly Conference Abstracts·2018
Wind turbine power curve modeling based on Gaussian Processes and Artificial Neural Networks
Renewable Energy·2018· 127 cited
0325722A/B - VORKAST: Optimierung Wind/PV mit Kürzestfristvorhersagen
Open MIND·2018Open Access
Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks
Atmospheric measurement techniques·2017· 87 citedOpen Access
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Frequent Co-authors

Jürgen Schmidhuber(11), Lukas Klass(11), Alexander Kabza(11), Markus Hölzle(10), Martin Felder(9), Katharina Strecker(9), Anton Kaifel(8), Ulrich Rührmair(6), Jan Sölter(6), Laurin Holz(6), Gideon Dror(4), Srinivas Devadas(4), Christian Osendorfer(4), Thomas Rückstieß(4), Kay Ohnmeiß(4), Leon Schröder(4), Alex Graves(3), Patrick Heinemann(3), Felix Streichert(3), Andreas Zell(3)